Chat Mining for Gender Prediction

Abstract. The aim of this paper is to investigate the feasibility of predicting the gender of a text document’s author using linguistic evidence. For this purpose, term- and style-based classification techniques are evaluated over a large collection of chat messages. Prediction accuracies up to 84.2% are achieved, illustrating the applicability of these techniques to gender prediction. Moreover, the reverse problem is exploited, and the effect of gender on the writing style is discussed.

• Type: Conference
• Year: 2006
• Where: ADVIS
• Authors: Tayfun Kucukyilmaz, Berkant Barla Cambazoglu, Cevdet Aykanat, Fazli Can
• Keywords: ADVIS 2006, Gender, Information Systems, Style-based Classification Techniques, Text Document Author